328 lines
26 KiB
TeX
328 lines
26 KiB
TeX
\chapterquote{Moxie Marlinspike~\cite{marlinspikeWeShouldAll2013}, see also
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\textcite{rogawayMoralCharacterCryptographic2015}}{
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We can only desire based on what we know. It is our present experience of what we are and are not able to do that
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largely determines our sense for what is possible. This is why same sex relationships, in violation of sodomy laws,
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were a necessary precondition for the legalization of same sex marriage. This is also why those maintaining
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positions of power will always encourage the freedom to talk about ideas, but never to act.}
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\chaptertitle{Case Study: Multiparty Computation in Scalable Hardware Security Modules}
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\label{chapter-smpc}
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Inertial Hardware Security Modules do not only support much larger payloads compared to conventional HSMs, they also
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support much higher power dissipation since they allow for direct air cooling of their payload. The tamper-sensing
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membrane of a conventional HSM must be continuous to provide security, so any heat dissipated by the payload must pass
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through it. Since the polymers used in tamper sensing membranes are poor conductors of heat, and since security benefits
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from a thicker tamper sensing assembly (cf.\ Chapter~\ref{chapter-survey}), power dissipation in conventional HSMs is
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limited~\cite{
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petriePartIITechnical,
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curetHardwareSecurityModule2025,
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zhangTamperrespondentAssembliesPorous2023,
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dragoneVentedTamperrespondentAssemblies2020}.
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Because IHSMs rotate at high speed, IHSM meshes do not need to be contiguous to provide adequate security. While a
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non-contiguous rotating mesh might theoretically allow a stationary attack tool to quickly penetrate, then retract
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through one of the mesh's gaps while the mesh is rotating, the time available for such an attack would be too short for
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a practical attack (cf.\ Chapter~\ref{chapter-ihsm}). For a mesh with three vertical connecting segments (cf.\
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Figure~\ref{fig_proto_mesh} in Chapter~\ref{chapter-ihsm}) rotating at \qty{1000}{\rpm}, this time would be in the order
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of \qty{20}{\milli\second}. Conventional HSM monitoring circuits would likely require a similar amount of time to react
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to an attack~\cite{obermaier2018}.
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Similar to how the increase in payload \emph{size} of IHSMs compared to conventional HSMs unlocks new applications such
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as the Quantum Key Distribution relay use case we presented in Chapter~\ref{chapter-qkd}, the increase in sustainable
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power dissipation enabled by air cooling also unlocks a number of new applications. Especially applications that require
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large amounts of computing power benefit from IHSM technology, as their needs fundamentally cannot be met by
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conventional HSMs.
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One such application that does not translate to conventional HSMs due to its need for large amounts of computing power
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is Multiparty Computation (MPC). MPC is a cryptographic construct that allows several networked parties to jointly
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perform a computation in such a way that the inputs to the computation remain private to the parties providing them, and
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no single party must be trusted for the computation to produce the correct result. Conceptually, MPC is similar to a
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secret sharing scheme that shares not just data, but computation between untrusted parties. The computation primitive
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MPC offers is a cryptographic tool for bootstrapping trust in a distributed computing system.
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We can deconstruct the problem of trust in computing into two largely disjunct parts: Establishing trust in a computing
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system during its creation is one, and maintaining this trust throughout its life is the other. For the second part of
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this problem, maintaining trust in a system once trusted, we have an ample supply of good methods such as encryption,
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authentication, and formally proven protocols. In contrast, establishing trust in a computing system is largely
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intractable and despite a large corpus of academic research on approaches such as hardware trojan detection and
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physicaly unclonable functions, only two approaches find practical adoption: In one, we build the system ourselves from
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the ground up, making sure to leave no part vulnerable to third-party compromise. In the other, we go to a store and
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physically buy a randomly-chosen computer using cash, assuming that while an attacker can target any particular system,
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they cannot target all systems simultaneously and we give them too little time to target the system we buy.
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A limitation of both approaches is that in either case, while the party creating or acquiring the system can trust it,
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they cannot prove its trustworthiness to other parties. MPC solves this issue by allowing every party to contribute
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their own trusted system to the protocol, cryptographically bootstrapping common trust in the computation and its
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output\footnote{
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In fact, MPC does more than just bootstrapping from each participant trusting their own system to a trusted shared
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computation. In an MPC protocol providing semi-honest or better security, MPC even \emph{relaxes} each party's trust
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requirement from trusting their own system to trusting any $n$-of-$k$ out of all systems contributing to the
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protocol.
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}.
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\section{Fast MPC and Slow HSMs}
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MPC is a uniquely powerful cryptographic primitive, yet it has still not found widespread practical adoption. To a large
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extent, this is because MPC is extremely resource-intensive to run. MPC protocols exist on a continuum trading off
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between extreme memory and bandwidth requirements on one end and intense computational requirements on the other end. At
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a first glance, MPC and Hardware Security Modules look like they would complement each other well, but HSMs cannot keep
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up with the computational requirements posed by MPC.
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Using P-256 curve ECC key generation as a benchmark, commercially available HSMs are quoted to perform between 3,500 and
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22,000 cryptographic operations per second~\cite{
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kumarIBMZ16Performance2025,
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ThalesLunaNetwork2024,
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Utrust_GP_HSM_Se_Series_Datasheet_ENpdf,
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}. Meanwhile, an MPC protocol doing something as simple as a single AES encryption, corresponding to 7,000 logic
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gates~\cite{wangGlobalScaleSecureMultiparty2017}, requires tens of thousands of cryptographic operations when performed
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in MPC. As a result, applying conventional HSMs to MPC at any practical scale is infeasible by multiple orders of
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magnitude. Literature on MPC commonly uses server hardware as a platform for benchmarks, which has power dissipation and
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processing speeds well beyond that of conventional HSMs.
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HSMs are slow compared to contemporary computers because they are limited in their power dissipation, and power
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dissipation is largely proportional to processing speed. In the limited fields where HSMs have found commercial
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application, this limitation was never considered important and market forces pushing towards faster HSMs appear to
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remain light with the issue receiving little attention in either academic or manufacturer publications on the topic.
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Fundamentally, conventional HSMs must envelope the entire payload in a tamper sensing mesh to detect drilling attacks,
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but a tamper sensing mesh that is impermeable to a drill is also impermeable to air. As a result, any heat conducted
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from the HSMs processor to the outside world must pass through the mesh. At the same time, the mesh cannot be thinned
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either because thinning it would enable micro-drilling attacks. The result of these constraints is a high thermal
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resistance between the HSM's processor and an external heat sink, which limits maximum power dissipation to a fraction
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of that of modern CPUs or even GPUs.
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A secondary limitation of conventional HSMs is that the highly specialized tamper sensing foils used in their
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construction often cannot be scaled to arbitray sizes without incurring unsustainable process yields due to the
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multiplication of error rates with increasing area. As a result, even if the heat dissipation problem could be solved,
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manufacturing the tamper sensing foil for a conventional HSM large enough to contain a more powerful CPU might not be
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possible. The HSM's tamper-sensing envelope would have to protect not only the CPU itself, but also its supporting
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components such as memory, power supplies and any internal heat spreading components.
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Inertial HSMs solve this issue since they allow their payload to be air cooled without compromising security, and they
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expand the feasible security boundary size from the several hundred milliliters offered by conventional HSMs to several
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liters and more, enabling the integration of standard, off-the-shelf server components such as mainboards, CPUs, CPU
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coolers, and power supplies. In this chapter, we will first provide a short overview illustrating a basic MPC protocol
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for context before elaborating a design of an IHSM tailored to MPC tasks. We will conclude with an outlook of
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applications unlocked by our design as well as promising areas for future improvements of our design.
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\section{The Fundamentals of Multiparty Computation}
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Secure Multiparty Computation can be separated into two broad classes of approaches: Garbled Circuits, and Secret
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Sharing-based techniques. Garbled Circuit techniques model the computation as a circuit of binary logic components such
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as logic gates. They are well-suited for implementing cryptographic primitives such as conventional symmetric ciphers
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such as AES or hash functions such as the SHA-2 series. Secret Sharing-based techniques model computation as an
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arithmetic circuit made from components such as arithmetic operations. While they can also work in binary, they often
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support operations on larger finite fields. Secret sharing-based techniques are efficient processing integer numbers,
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but can have higher overhead in processing using many bitwise operations such as ciphers or cryptographic hash
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functions\cite{evansPragmaticIntroductionSecure}.
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\subsection{Security Models in MPC}
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MPC schemes are usually evaluated assuming one of three adversary levels: \emph{Semi-Honest}, \emph{Covert} or
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\emph{Malicious} adversaries. A \emph{Semi-Honest} adversary is an adversary that follows the protocol as specified, but
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that outside the protocol's execution may collude arbitrarily with other parties to reveal the secret inputs of other
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parties. A \emph{Covert} adversary is an adversary that additionally may cheat during the protocol's execution, but only
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in ways that cannot be detected by other parties. Finally, a \emph{Malicious} adversary is one that can deviate from
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the protocol's execution arbitrarily~\cite{aumannSecurityCovertAdversaries2010}. The covert adversary model most closely
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captures the requirements of a real-world scenario where a small number of cooperating parties runs the protocol, since
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in such settings cheating parties can easily be excluded once identified. The malicious adversary model captures
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real-world settings where parties do not have stable identities such as peer-to-peer settings. The semi-honest model is
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mostly interesting as a research tool since protocols assuming a semi-honest adversary can often be upgraded to covert
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or malicious security at some performance tradeoff. In a practical setting, a semi-honest secure MPC protocol would not
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provide additional security over just having one party run the computation except in some situations where inadvertent
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side-channel leakage is a concern. Using HSMs to secure protocol participants' cryptographic computations complements
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both the covert and malicious security models.
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\subsection{Oblivious Transfer}
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Before we can go into details of multiparty computation, we need to define an important primitive. Oblivious Transfer is
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a cryptographic protocol between two parties that enables one party, the \emph{Sender}, to share one of two values to
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the other party, the \emph{Receiver}. The Receiver can choose which of the two values it wants to receive by inputting a
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choice bit $b$ into the protocol. After the protocol has been executed, the Receiver learns \emph{only} its chosen
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value, and learns nothing about the other input value that the Sender provided. Meanwhile, the Sender learns nothing
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about the choice bit $b$ of the receiver.
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\subsubsection{OT extensions}
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Oblivious Transfer is a public-key primitive, requiring asymmetric cryptographic operations. For this reason, ``raw''
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Oblivious Transfer is not particularly fast. In practice, this issue is solved by applying a technique called Oblivious
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Transfer Extensions (OTe)\cite{ishaiExtendingObliviousTransfers2003}. Using OTe, a fixed, small number of public-key
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base Oblivious Transfer instances can be extended into an arbitrarily large number of Oblivious Transfer instances using
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only invocations of a pseudo-random function (PRF) such as a cryptographic hash function.
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\subsection{A basic MPC protocol: Boolean MPC with Yao's Garbled Circuits}
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As a basic example of the approach taken by MPC protocols, we will give a brief overview of Yao's Garbled Circuits (GC)
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protocol. Yao's GC is one of the oldest Multiparty Computation protocols, dating back to the 1980ies. In Yao's GC, two
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parties jointly compute a function that is represented as a circuit of binary logic gates by evaluating the circuit gate
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by gate. In Yao's GC, one party, generator, creates a random \emph{garbled} representation of the circuit and sends it
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to the other party, the evaluator, who computes its output. The core idea in Yao's GC is that every wire $w_i$ in the
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circuit is assigned two random cryptographic secret keys $w_i^b$, called wire labels, one $w_i^0$ for the logical value
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$0$ and one $w_i^1$ for the value $1$. The mapping from logic values to these keys is assigned randomly by the
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generator, and unknown to the
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evaluator~\cite{yaoHowGenerateExchange1986,beaverComplexitySecureProtocols1990,evansPragmaticIntroductionSecure}.
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Gates are represented in Yao's GC as truth tables with one row for every combination of input wire values. Each row of
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these truth tables contains the output wire label (i.e. secret key) corresponding to the gate's logical output value for
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the row's combination of input values. The output wire label in each row is encrypted with \emph{both} input wire labels
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corresponding to this row as keys.
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The generator must indicate to the evaluator which row of a gate's truth table to decrypt, while also avoiding leaking
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the logical value of the output wire to the evaluator. This is commonly done in a technique called
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\emph{point-and-permute} where a random pointer bit $p_i^b$ is appended to each wire $w_i^b$ label such that $p_i^b =
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\neg p_i^{\neg b}$. The rows in the gate's truth table are ordered according to the combination of the two input wire
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labels' pointer bits. When the evaluator obtains the two input wire labels, they obtain their pointer bits, which
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combined are the index of the row to decrypt in the following gate's truth table.
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It is clear how the protocol described above can be used to compute any binary circuit, but there are two questions
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remaining: How do the two parties provide input into the circuit, and how do they decode the circuit's output? Output is
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handled in Yao's GC by creating an output decoding table for every output wire of the circuit. The output decoding table
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contains two rows, one for a logical $0$ output value and one for a logical $1$ output value. Each row contains the hash
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of the output wire's label corresponding to the row's logical output value. This way, the evaluator can identify the
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logical value knowing the output wire label, but is unable to deduce the output wire label from the output decoding
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table.
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Inputs are a bit more difficult to handle. While the generator can easily provide secret inputs by simply providing the
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evaluator with the input wire labels corresponding to its input, inputs from the evaluator require oblivious transfer to
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avoid leaking the evaluator's input to the generator. To input the logic bit $b$ on wire $w_i$, the generator and the
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evaluator perform an 1-out-of-2 oblivious transfer with the generator assuming the Sender role and providing the two
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input wire labels $w_i^0$ and $w_i^1$ as the two choices, and the evaluator submitting its chosen input bit $b$ as the
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OT's choice bit.
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Yao's GC has good performance since the only asymmetric cryptographic primitive used is in the Oblivious Transfer needed
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for the evaluator's hidden inputs. The generation and the evaluation of the garbled circuit itself both only require
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evaluations of a pseudorandom function such as a cryptographic hash or a cipher. Still, performing a computation using a
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Garbled Circuit is many times slower than performing it in the clear. Intuitively, each single-bit gate in the garbled
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circuit results in several cryptographic operations with input and output sizes of dozens or hundreds of bits.
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Practically useful functions such as AES encryption have circuit implementations measuring thousands or tens of
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thousands of gates, meaning these costs quickly escalate for practical problem
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sizes~\cite{boyarNewCombinationalLogic2010, songhoriTinyGarbleHighlyCompressed2015}.
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\section{A High-Performance IHSM for MPC Applications}
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Multiparty Computation is at the verge of being practical in some applications, but is still too computationally
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expensive for others. While some attempts at GPU-accelerating MPC primitives exist, in practice it is commonly
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implemented using CPU processing. The technology comes with an unavoidable increase in computational complexity since
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each single plaintext computation or gate results in several cryptographic operations.
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A naive implementation might attempt to implement MPC using an HSM by simply offloading all cryptographic operations to
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the HSM. In practice, this is not a workable solution due to the slow processing speed of conventional HSMs. In the near
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term, absent radical developments in either MPC theory or in the speed and power efficiency of processing hardware, the
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only feasible solution for HSM-protected MPC at any practical scale is to find a way to protect an entire server-class
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computer. IHSMs are a natural fit for this requirement since they allow for large, air-cooled payloads.
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As a baseline performance target, we consider a commodity server mainboard in CEB or ATX form factor, populated with a
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high-end server CPU and a large amount of RAM. As MPC systems do not usually require a great amount of storage, we can
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largely ignore storage for our size and power calculations. As a result, we end up with a total maximum power
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dissipation of approximately \qty{420}{\watt} as shown in Table~\ref{tab_power_budget}. Dissipating this amount of power
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using air cooling is within the capabilities of commodity server cooling
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components~\cite{coroamaPossibleFutureTrends2025}.
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\begin{table}
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\centering
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\begin{tabular}{r|l|r|r}
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Count & Component & Power Dissipation (approx.) & Total\\\hline
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1 & CPU & \qty{350}{\watt}~\cite{tropgen16YearsSPEC2024}&\qty{350}{\watt}\\
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16 & Memory~\cite{kennedyDDR4DIMMsSystem2017} &\qty{2}{\watt}&\qty{32}{\watt}\\
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1 & Losses & \qty{40}{\watt}&\qty{40}{\watt}\\
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\end{tabular}
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\caption[Power budget of a modern mid-range server.]{Power budget of a modern mid-range server. Losses were
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estimated at 10\%, consistent with mainboard losses plus losses from a 80plus platinum efficiency certified
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power supply (~94\% at load).}
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\label{tab_power_budget}
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\end{table}
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A common type of side-channel attack on cryptographic systems are power analysis attacks. In such attacks, the supply
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current of the target processing system is measured at high speed while the target is performing cryptographic
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computations. By aggregating the results of a large number of the resulting power traces, it is often possible to infer
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the value of secret data such as cryptographic keys. To mitigate this type of attack, we propose placing the system's
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power supply inside the IHSM envelope. A secondary benefit of placing the power supply inside the tamper-sensing barrier
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is that it simplifies the power wiring between the outside of the IHSM cage and the payload. Supplying the
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\qty{12}{\volt} power rails that commodity mainboard commonly use requires tens of Ampere. To carry such high current,
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the wiring has to be sized accordingly. In an IHSM, even thick wires can easily be passed through the mesh cage, but
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such wiring requires a large opening at the shaft on one end of the cage, which creates a literal security gap. Placing
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the power supply inside of the cage reduces the size of the wires needed since the power supply steps down a lower
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current \qty{240}{\volt} input to the system's high-current \qty{12}{\volt} rails. Using DIN VDE 0298-4\todo{Citation?}
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as a reference, a pair of \qty{1.5}{\milli\meter^2} conductors is sufficient for more than \qty{3}{\kilo\watt} of load
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under worst-case conditions.
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\subsection{Software Considerations}
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While the hardware of a HSM-assisted MPC system is a straightforward application of IHSM technology to a server
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platform, the software implementation poses some unique challenges. A core concern in an IHSM based on commodity
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hardware running a commodity operating system is the concrete implementation of the IHSM's alarm reseponse. When the
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IHSM detects tampering, it is crucial that all secrets in the payload have been made unusable before an attacker can
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either extract them, or stop the system from making them unusable.
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Making secret data unusable to an attacker can be done by either deleting it (\emph{zeroization} in HSM terminology) or
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by encrypting the data when it is stored and destroying the key. Zeroization is more technically challenging, while
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encryption comes at a performance cost. The main challenges in zeroization are ensuring that the data is deleted fast
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enough, and making sure it cannot be reconstructed through data remanence effects. Zeroization is practical for small
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amounts of RAM such as a microcontroller's main SRAM or a small amount of DRAM in a server set aside for cryptographic
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keys. For larger amounts of data, or for any data stored on flash memory, HDDs etc., encryption is the only viable
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option due to speed. Encrypting data at rest on HDD or flash storage is straightforward to do in software and is a
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standard feature in any modern operating system. RAM is more challenging. Encrypting data in RAM cannot be done in
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software without effectively running a system emulation and incurring a massive performance penalty. Recent CPUs from
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Intel and AMD contain hardware features that provide transparent DRAM encryption. These hardware features would be
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necessary when securing an entire sever in an MPC setup with IHSMS technology.
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\subsection{A Joint Cooling and IHSM Envelope Powertrain}
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In this section, we will present a sketch of a design for an IHSM envelope large enough to fit a small server mainboard,
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and that provides air cooling to the payload. Our sketch solves the engineering issue of moving such an IHSM envelope
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while simultaneously providing cooling to the payload.
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\begin{figure}
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\centering
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\begin{subfigure}{0.45\textwidth}
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\centering
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\includegraphics[width=\textwidth]{setup_0001.jpg}
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\caption{}
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\label{fig_setup_left}
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\end{subfigure}
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\hspace*{5mm}
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\begin{subfigure}{0.45\textwidth}
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\centering
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\includegraphics[width=\textwidth]{setup_0002.jpg}
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\caption{}
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\label{fig_setup_right}
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\end{subfigure}
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\caption{Conceptual demonstrator of the fan-driven IHSM primary mesh approach.}
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\label{fig_setup}
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\end{figure}
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Our proposed design is based on the idea of using the cooling fans' airflow to power the rotation of the IHSM envelope.
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Figure~\ref{fig_setup} shows a conceptual demonstration of this approach. Using a basic cylindrical design, the IHSM
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envelope consists of two discs above and below the payload that are connected through vertical struts on the outside of
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the payload. We propose widening these vertical connecting struts, and angling them such that the entire envelope
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becomes a centrifugal impeller. By letting air flow into the envelope from the side, and back out through its top and
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bottom, the envelope assumes the same configuration used in centrifugal cooling fans. Tamper sensing meshes are placed
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inside the vertical struts as well as along the horizontal discs at the top and at the bottom.
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Laying out an IHSM this way has several advantages. First, we save some vertical space by removing the motor from the
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shaft of the mesh. Second, on top of driving the mesh, the airflow also serves to cool the payload. Finally, this
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approach eliminates the motor driving the mesh as a single point of failure. In a basic IHSM design as we introduced it
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in Chapter~\ref{chapter-ihsm}, this motor is a critical component as its failure would lead to the mesh accelerometer
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triggering the deceleration tamper alarm. Using a brushless motor type the number of wear components in this motor can
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be reduced to the motor's shaft bearings. A complication in the practical manufacturing of IHSMs at a small scale is
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that small-scale production does not allow for a custom-made motor. Limiting the selection to off-the-shelf brushless
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motors leads to an unpredictability of bearing life due to the cost of precision bearings. Complicating things, bearing
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specifications are not usually included in motor datasheets.
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Compared to the market for off-the-shelf small brushless motors, cooling fans are easier to shop for. A large selection
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of products with various form factors and specifications is available, and manufacturers usually give detailed
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information on both performance and lifetime. Industrial and server cooling fans are commonly rated for uninterrupted
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24/7 operation. The cooling fans can be located on the outside of the envelope in an easily accessible location. Like in
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many servers, they can be set up in a redundant way such that a failed cooling fan can be replaced while the system
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continues to operate.
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The main drawback of a fan-driven IHSM is the amount of airflow necessary. To maximize payload volume, the fan blades
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must be kept as narrow as possible. Narrow fan blades work best at high air speed, but high air speed requires the fan
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to have high airflow. Besides limiting fan selection and increasing power consumption, high airflow fans also are noisy.
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Despite these limitations, we consider fan-driven IHSMs a valid tradeoff since such a system would most likely be
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deployed in a datacenter where high noise levels are acceptable.
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\section{Outlook}
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In this chapter we briefly introduced the challenges raised by MPC at scale, and we outlined a practical solution based
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on an IHSM-protected sever that can be used to perform MPC with an unique combination of high bandwidth and low latency
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that was previously considered impractical due to physical security concerns.
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